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20242026
most citedAI Must Embrace Specialization via Superhuman Adaptable Intelligence

1 citations · 1 across the 9 of their papers we have counts for

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cs.AI2026

The Spike, the Sparse and the Sink: Anatomy of Massive Activations and Attention Sinks

Shangwen Sun, Alfredo Canziani, Yann LeCun +1

We study two recurring phenomena in Transformer language models: massive activations, in which a small number of tokens exhibit extreme outliers in a few channels, and attention si…

cs.AI2026

AI+HW 2035: Shaping the Next Decade

Deming Chen, Jason Cong, Azalia Mirhoseini +27

Artificial intelligence (AI) and hardware (HW) are advancing at unprecedented rates, yet their trajectories have become inseparably intertwined. The global research community lacks…

cs.AI20261 cited

AI Must Embrace Specialization via Superhuman Adaptable Intelligence

Judah Goldfeder, Philippe Wyder, Yann LeCun +1

Everyone from AI executives and researchers to doomsayers, politicians, and activists is talking about Artificial General Intelligence (AGI). Yet, they often don't seem to agree on…

cs.AI2026

Learning Latent Action World Models In The Wild

Quentin Garrido, Tushar Nagarajan, Basile Terver +3

Agents capable of reasoning and planning in the real world require the ability of predicting the consequences of their actions. While world models possess this capability, they mos…

cs.AI2025

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Mido Assran, Adrien Bardes, David Fan +27

A major challenge for modern AI is to learn to understand the world and learn to act largely by observation. This paper explores a self-supervised approach that combines internet-s…

cs.AI2025

Multi-modal AI for comprehensive breast cancer prognostication

Jan Witowski, Ken G. Zeng, Joseph Cappadona +48

Treatment selection in breast cancer is guided by molecular subtypes and clinical characteristics. However, current tools including genomic assays lack the accuracy required for op…